QuantGPT Local Runner
Local WebSocket-capable runner for QuantGPT experiments.
Usage
pip install quantgpt-local-runner
quantgpt-run-local --port 8000 --host 0.0.0.0 --log-level debug
WebSocket
- Endpoint:
/ws - Send JSON with a
codefield containing Python to execute.
Example message:
{"code": "print('hello world')"}
Response:
{"status":"completed","content":"hello world\n","timestamp":"..."}
Notes
- If available,
numpy,pandas, andvectorbtproare imported into the execution namespace asnp,pd, andvbt.
Metadata
Release files for quantgpt-local-runner 0.2.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| quantgpt_local_runner-0.2.2.tar.gz | 4.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| quantgpt_local_runner-0.2.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.5 kB
Release files / quantgpt_local_runner-0.2.2.tar.gz
| Download URL | quantgpt_local_runner-0.2.2.tar.gz |
|---|---|
| Size | 4.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.1.0 CPython/3.10.3
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Release files / quantgpt_local_runner-0.2.2-py3-none-any.whl
| Download URL | quantgpt_local_runner-0.2.2-py3-none-any.whl |
|---|---|
| Size | 6.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.10.3
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